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Explaining The Efficacy of Counterfactually Augmented Data

Explaining The Efficacy of Counterfactually Augmented Data

5 October 2020
Divyansh Kaushik
Amrith Rajagopal Setlur
Eduard H. Hovy
Zachary Chase Lipton
    CML
ArXivPDFHTML

Papers citing "Explaining The Efficacy of Counterfactually Augmented Data"

29 / 29 papers shown
Title
On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs
On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs
Nitay Calderon
Roi Reichart
40
10
0
27 Jul 2024
ACCORD: Closing the Commonsense Measurability Gap
ACCORD: Closing the Commonsense Measurability Gap
François Roewer-Després
Jinyue Feng
Zining Zhu
Frank Rudzicz
LRM
48
0
0
04 Jun 2024
Data Augmentations for Improved (Large) Language Model Generalization
Data Augmentations for Improved (Large) Language Model Generalization
Amir Feder
Yoav Wald
Claudia Shi
S. Saria
David M. Blei
OOD
CML
32
7
0
19 Oct 2023
Out-of-Distribution Generalization in Text Classification: Past,
  Present, and Future
Out-of-Distribution Generalization in Text Classification: Past, Present, and Future
Linyi Yang
Yangqiu Song
Xuan Ren
Chenyang Lyu
Yidong Wang
Lingqiao Liu
Jindong Wang
Jennifer Foster
Yue Zhang
OOD
37
2
0
23 May 2023
Learning to Generalize for Cross-domain QA
Learning to Generalize for Cross-domain QA
Yingjie Niu
Linyi Yang
Ruihai Dong
Yue Zhang
21
6
0
14 May 2023
AutoCAD: Automatically Generating Counterfactuals for Mitigating
  Shortcut Learning
AutoCAD: Automatically Generating Counterfactuals for Mitigating Shortcut Learning
Jiaxin Wen
Yeshuang Zhu
Jinchao Zhang
Jie Zhou
Minlie Huang
CML
AAML
22
8
0
29 Nov 2022
GLUE-X: Evaluating Natural Language Understanding Models from an
  Out-of-distribution Generalization Perspective
GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective
Linyi Yang
Shuibai Zhang
Libo Qin
Yafu Li
Yidong Wang
Hanmeng Liu
Jindong Wang
Xingxu Xie
Yue Zhang
ELM
44
79
0
15 Nov 2022
Pneg: Prompt-based Negative Response Generation for Dialogue Response
  Selection Task
Pneg: Prompt-based Negative Response Generation for Dialogue Response Selection Task
Nyoungwoo Lee
chaeHun Park
Ho-Jin Choi
Jaegul Choo
27
6
0
31 Oct 2022
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer
  Data Augmentation
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation
Phillip Howard
Gadi Singer
Vasudev Lal
Yejin Choi
Swabha Swayamdipta
CML
58
25
0
22 Oct 2022
Augmentation by Counterfactual Explanation -- Fixing an Overconfident
  Classifier
Augmentation by Counterfactual Explanation -- Fixing an Overconfident Classifier
Sumedha Singla
Nihal Murali
Forough Arabshahi
Sofia Triantafyllou
Kayhan Batmanghelich
CML
59
4
0
21 Oct 2022
Robustifying Sentiment Classification by Maximally Exploiting Few
  Counterfactuals
Robustifying Sentiment Classification by Maximally Exploiting Few Counterfactuals
Maarten De Raedt
Fréderic Godin
Chris Develder
Thomas Demeester
13
1
0
21 Oct 2022
On Feature Learning in the Presence of Spurious Correlations
On Feature Learning in the Presence of Spurious Correlations
Pavel Izmailov
Polina Kirichenko
Nate Gruver
A. Wilson
36
117
0
20 Oct 2022
FactMix: Using a Few Labeled In-domain Examples to Generalize to
  Cross-domain Named Entity Recognition
FactMix: Using a Few Labeled In-domain Examples to Generalize to Cross-domain Named Entity Recognition
Linyi Yang
Lifan Yuan
Leyang Cui
Wen Gao
Yue Zhang
23
15
0
24 Aug 2022
Challenges in Applying Explainability Methods to Improve the Fairness of
  NLP Models
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models
Esma Balkir
S. Kiritchenko
I. Nejadgholi
Kathleen C. Fraser
21
36
0
08 Jun 2022
Necessity and Sufficiency for Explaining Text Classifiers: A Case Study
  in Hate Speech Detection
Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection
Esma Balkir
I. Nejadgholi
Kathleen C. Fraser
S. Kiritchenko
FAtt
38
27
0
06 May 2022
Towards Fine-grained Causal Reasoning and QA
Towards Fine-grained Causal Reasoning and QA
Linyi Yang
Zhen Wang
Yuxiang Wu
Jie Yang
Yue Zhang
41
15
0
15 Apr 2022
Informativeness and Invariance: Two Perspectives on Spurious
  Correlations in Natural Language
Informativeness and Invariance: Two Perspectives on Spurious Correlations in Natural Language
Jacob Eisenstein
CML
33
25
0
09 Apr 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious
  Correlations
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
Polina Kirichenko
Pavel Izmailov
A. Wilson
OOD
49
318
0
06 Apr 2022
A Rationale-Centric Framework for Human-in-the-loop Machine Learning
A Rationale-Centric Framework for Human-in-the-loop Machine Learning
Jinghui Lu
Linyi Yang
Brian Mac Namee
Yue Zhang
27
39
0
24 Mar 2022
Diffusion Causal Models for Counterfactual Estimation
Diffusion Causal Models for Counterfactual Estimation
Pedro Sanchez
Sotirios A. Tsaftaris
DiffM
BDL
35
69
0
21 Feb 2022
Making a (Counterfactual) Difference One Rationale at a Time
Making a (Counterfactual) Difference One Rationale at a Time
Michael J. Plyler
Michal Green
Min Chi
21
11
0
13 Jan 2022
Connecting degree and polarity: An artificial language learning study
Connecting degree and polarity: An artificial language learning study
Lisa Bylinina
Alexey Tikhonov
Ekaterina Garmash
AI4CE
14
0
0
13 Sep 2021
Causal Inference in Natural Language Processing: Estimation, Prediction,
  Interpretation and Beyond
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond
Amir Feder
Katherine A. Keith
Emaad A. Manzoor
Reid Pryzant
Dhanya Sridhar
...
Roi Reichart
Margaret E. Roberts
Brandon M Stewart
Victor Veitch
Diyi Yang
CML
41
234
0
02 Sep 2021
An Investigation of the (In)effectiveness of Counterfactually Augmented
  Data
An Investigation of the (In)effectiveness of Counterfactually Augmented Data
Nitish Joshi
He He
OODD
19
46
0
01 Jul 2021
On the Efficacy of Adversarial Data Collection for Question Answering:
  Results from a Large-Scale Randomized Study
On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study
Divyansh Kaushik
Douwe Kiela
Zachary Chase Lipton
Wen-tau Yih
AAML
11
36
0
02 Jun 2021
Counterfactual Invariance to Spurious Correlations: Why and How to Pass
  Stress Tests
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests
Victor Veitch
Alexander DÁmour
Steve Yadlowsky
Jacob Eisenstein
OOD
24
91
0
31 May 2021
A Survey of Data Augmentation Approaches for NLP
A Survey of Data Augmentation Approaches for NLP
Steven Y. Feng
Varun Gangal
Jason W. Wei
Sarath Chandar
Soroush Vosoughi
Teruko Mitamura
Eduard H. Hovy
AIMat
39
799
0
07 May 2021
Hypothesis Only Baselines in Natural Language Inference
Hypothesis Only Baselines in Natural Language Inference
Adam Poliak
Jason Naradowsky
Aparajita Haldar
Rachel Rudinger
Benjamin Van Durme
190
576
0
02 May 2018
Adversarial Example Generation with Syntactically Controlled Paraphrase
  Networks
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks
Mohit Iyyer
John Wieting
Kevin Gimpel
Luke Zettlemoyer
AAML
GAN
205
712
0
17 Apr 2018
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